IB Maths AI HL
Further Differentiation
Paper 1 & 2
~6 min read
Second Order Derivatives
Differentiate once and you get the gradient. Differentiate the gradient and you get the second derivative β the rate of change of the rate of change. It tells you how the gradient itself is shifting, which is exactly what you need to classify stationary points and read a curve’s concavity in the topics ahead.
π What you need to know
- Second derivative = differentiate the function twice.
- Two notations: dΒ²ydxΒ² and fβ²β²(x) β note where the 2’s sit.
- Meaning: the rate of change of the gradient.
- Used to: test stationary points, determine concavity, and help graph fβ².
- Method: just differentiate again β often rewriting roots/fractions as powers first.
- Take care with negative and fractional powers on the second pass.
What the notation means
The first derivative is the gradient; the second is the gradient’s gradient. Watch where the superscript 2’s go β they sit differently in the two parts of the fraction.
First and second derivative notation
dydx = fβ²(x) (first) Β· dΒ²ydxΒ² = fβ²β²(x) (second)
β notation to recognise, not a booklet formula
π§ “d-two-y over d-x-squared”
You differentiate twice (so dΒ²) with respect to x twice (so xΒ²). The 2 sits up top with the d, but down below with the x β that asymmetry is the thing to memorise.
| Derivative | What it measures |
|---|
| f(x) | the value of the function |
| fβ²(x) (first) | the gradient β the rate of change of f |
| fβ²β²(x) (second) | the rate of change of the gradient |
Why it’s useful: the second derivative lets you test for local minimum and maximum points, decide the nature of stationary points, determine the concavity of a curve, and help sketch the graph of the derivative β all coming up in the next two topics.
Finding a second derivative
π§ Recipe β second derivative
- Rewrite roots and fractions as negative/fractional powers of x.
- Differentiate once to get fβ²(x) β applying chain/product/quotient rules as needed.
- Differentiate again to get fβ²β²(x), working carefully term by term.
- Evaluate or simplify if asked β e.g. tidy surds by rationalising the denominator.
π€ Why are negative powers so error-prone here?
Each differentiation drops the power by 1, so a term like xβ1/2 becomes xβ3/2, then xβ5/2 β the exponents get more negative and the coefficients pick up extra factors each time. Two passes means twice the chance to slip a sign or mishandle the fraction, so the safest approach is one clean term at a time.
Worked examples
Throughout, f(x) = 4 β βx + 3βx.
WE 1Rewrite f(x) as powers of x
Convert the roots before differentiating.
βx = x^(1/2), 3βx = 3x^(β1/2)
f(x) = 4 β x^(1/2) + 3x^(β1/2)
Differentiate once, term by term.
4 β 0
βx^(1/2) β βΒ½x^(β1/2)
3x^(β1/2) β 3Β·(βΒ½)x^(β3/2) = β32x^(β3/2)
fβ²(x) = βΒ½x^(β1/2) β 32x^(β3/2)
Differentiate fβ²(x) again. Watch the negatives.
βΒ½x^(β1/2) β βΒ½Β·(βΒ½)x^(β3/2) = ΒΌx^(β3/2)
β32x^(β3/2) β β32Β·(β32)x^(β5/2) = 94x^(β5/2)
fβ³(x) = ΒΌx^(β3/2) + 94x^(β5/2)
WE 4Evaluate fβ²β²(3) in the form aβb
Write as surds, substitute x = 3, then rationalise.
fβ³(x) = 14xβx + 94xΒ²βx
fβ³(3) = 112β3 + 936β3 = 1236β3 = 13β3
rationalise: 13β3 Γ β3β3 = β39
fβ³(3) = 19β3
WE 5Find fβ²β²(x) for f(x) = 2x3 β 5x2 + 4x β 1
A polynomial β straightforward double differentiation.
fβ²(x) = 6xΒ² β 10x + 4
fβ³(x) = 12x β 10
fβ³(x) = 12x β 10
π‘ Top tips
- Rewrite first β convert roots and fractions to powers before differentiating.
- Go term by term β second derivatives are where careless slips happen.
- Mind the 2’s in the notation: dΒ²ydxΒ² (up with d, down with x).
- Rationalise surds when a question wants the form aβb.
- Apply the right rule each pass β chain/product/quotient may be needed both times.
- Sanity-check the sign β it’ll tell you concavity later, so it matters.
β Common mistakes
- Power-rule slips on the second pass β xβ1/2 β xβ3/2, not xβ1/2.
- Sign errors β two negatives multiply to a positive (e.g. βΒ½Β·βΒ½ = +ΒΌ).
- Misplacing the 2’s β it’s dΒ²ydxΒ², not dyΒ²dxΒ².
- Stopping at fβ² β read carefully; the question wants the second derivative.
- Leaving surds un-rationalised when a specific form is requested.
Next up β Stationary Points. With both first and second derivatives in hand, you can now do more than just find stationary points (where fβ²(x) = 0) β you can classify them. The next topic uses the sign of fβ²β²(x) to decide instantly whether a turning point is a local minimum, a local maximum, or something subtler.
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